EP1288835A1 - Un procédé pour définir des études de gene hunting - Google Patents

Un procédé pour définir des études de gene hunting Download PDF

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Publication number
EP1288835A1
EP1288835A1 EP01650098A EP01650098A EP1288835A1 EP 1288835 A1 EP1288835 A1 EP 1288835A1 EP 01650098 A EP01650098 A EP 01650098A EP 01650098 A EP01650098 A EP 01650098A EP 1288835 A1 EP1288835 A1 EP 1288835A1
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European Patent Office
Prior art keywords
population
study
test
gene
hunting
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EP01650098A
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German (de)
English (en)
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Fabian Sievers
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Hitachi Ltd
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Hitachi Ltd
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Priority to EP01650098A priority Critical patent/EP1288835A1/fr
Priority to JP2002085475A priority patent/JP2003070500A/ja
Priority to PCT/IE2002/000129 priority patent/WO2003019451A1/fr
Publication of EP1288835A1 publication Critical patent/EP1288835A1/fr
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/40—Population genetics; Linkage disequilibrium

Definitions

  • the present invention relates to a method and system for defining gene hunting studies.
  • a crucial first step in finding diseased loci that contribute to a genetic disease is to demonstrate linkage with a gene or DNA sequence of known location, namely, a marker.
  • Various methods have been used such as population association between disease and a marker.
  • population association between disease and a marker.
  • association can occur in the absence of linkage, for example, as a result of population stratification.
  • tests that do not depend on association have been carried out by, for example, family-based controls tests or transmlssion/disequilibrium tests.
  • the first major problem is to ensure that the particular analysis methodology which will generally be analysis software, has been correctly designed so that when used on the data, it should produce the desired result. Secondly, one has to then be assured that the actual experiment design itself is correct. The two essentially go hand in hand in the sense that if the analysis software is flawed, then it does not matter how well the experiment is being designed and carried out as the results will be flawed. Similarly, even if the analysis software is correct and well designed, if the actual study itself has been badly designed, then the experiments will fail. The gene hunting study therefore depends on both of these.
  • the present invention is directed towards solving these problems.
  • a method of defining a gene hunting study to determine certain genetic data comprising:-
  • the advantage of this is that one can carry out the gene hunting study theoretically to decide whether such a gene hunting study is likely to be successful. If carried out in practice, it is possible that having taken some of the theoretical patient population to carry out the gene hunting study, it would quickly be apparent that such a gene hunting study would not lead to a result that could be relied on and therefore a larger part of the theoretical patient population would then be used to carry out the gene hunting study of the invention again until a satisfactory result was achieved. Then, it would be possible for the researcher to define and design the practical gene hunting study with a measure of confidence or to decide it was not practical to carry it out.
  • the generation of the test population comprises:-
  • the recombination fraction assigned to the test locus is obtained by taking a portion of the recombination fraction of the two adjacent markers.
  • the recombination fraction assigned is half the recombination fraction of the two adjacent markers. It is also possible to assign more than one test locus between adjacent markers and when this is done, the sum of the recombination fractions is a proportion of the recombination fraction between the markers and cannot be more than the latter fraction.
  • test population is chosen after many generations of evolution.
  • test population When the test population is being generated, at predetermined numbers of generations, a correlation between reference alleles and other alleles is determined and when the correlation is determined to be satisfactory, the test population is chosen to be that size for extraction of a patient size for the subsequent study.
  • the size of the initial population may be varied and the test population determined for different sizes of initial population.
  • the mutation may be introduced in the initial population or many generations beyond the initial population or indeed, at a number of loci.
  • the size of the theoretical population is varied to determine the size of a subsequent real patent population for the actual gene hunting study.
  • test population provides a theoretical patient population whose size relative to the test population is less than the relative size of the actual patient population the mutation is introduced at at least one additional locus and a new theoretical patient population produced.
  • test population provides a theoretical patient population whose size relative to the test population is greater than the relative size of the actual patient population the size of the initial population is increased and a new test population produced.
  • the efficacy of the gene hunting study in the theoretical patient population is assessed by using a gene hunting study testing methodology.
  • the invention provides a method in which an actual gene hunting study including the specification of the loci of reference alleles and size of patient population is defined when a gene study on a theoretical patient population provides an apparently successful study.
  • the method comprises:-
  • the invention may provide theoretical gene hunting studies produced by the method as well as an actual gene hunting study which has been defined by the method.
  • the invention provides a system for control of a gene hunting study to determine certain genetic data including a server comprising:
  • the system may also comprise means to carry out a gene hunting study on at least part of the theoretical patient population and additionally may comprise means to carry out a study testing methodology.
  • the invention is envisaged being provided on a computer and ideally the invention will be embodied in a computer program comprising program instructions for causing a computer to run the method as laid out above or indeed, to perform the means for the system as laid out above.
  • a computer program may be embodied on a record medium, a computer memory, a read only memory or carried on an electrical signal carrier.
  • the invention is a relatively simple one. What is done is to prepare an artificial population, using a population generator such as a suitably programmed computer, for example, one could generate four million individuals, forty thousand of whom have a particular genetic disorder, beginning maybe 1,000 years ago with an initial population of 1,000 where one or more of the individuals in that 1,000 initial population would have this particular genetic disorder. The impact of the initial population is that it determines the percentage of affected individuals in the final population in which the patient population is embedded.
  • a population generator such as a suitably programmed computer, for example, one could generate four million individuals, forty thousand of whom have a particular genetic disorder, beginning maybe 1,000 years ago with an initial population of 1,000 where one or more of the individuals in that 1,000 initial population would have this particular genetic disorder.
  • the impact of the initial population is that it determines the percentage of affected individuals in the final population in which the patient population is embedded.
  • What has been done is to define an initial population for generation of a test population, which test population will in turn provide a patient population of affected individuals. That patient population can then be used to determine
  • the population generator can be used in two ways. Firstly, the artificial data can be sent to a test to analyse the software design and development and until that software for analysing the data has been shown to be accurate, the particular test methodology is not used. This is identified by the area surrounded by the interrupted lines and identified by the reference numeral 1. Once we are satisfied that the particular methodology is a suitable methodology, then it can be used in the experiments. Very often, it will not be necessary check such methodology because it will have already been checked both practically and theoretically. However, it can be said that this particular testing of the algorithms and analysis process is useful as a backup to the experiments.
  • the main purpose of the population generator is illustrated in the portion of the drawing of Fig. 1, identified by the reference numeral 2.
  • a particular experiment design is chosen and the artificial data generated by the population generator is used to test the experiment design and all aspects of the experiment can be altered using the artificial data and in each case testing it.
  • This is a much cheaper way of testing the design which can be done iteratively until it is decided that the particular experiment design, i.e. the definition of the gene hunting study, would lead to useful results in which case the necessary number of real patients is chosen and the real gene hunting study takes place on them.
  • the purpose of the invention is to produce genetic information that is correlated with the particular reference points quickly and accurately.
  • Fig. 2 there is illustrated, in simple form, the hardware requirements for carrying out the invention which comprises an input device 10, a memory 11, a CPU 12 and a display 13. Any suitable computer can be used.
  • the CPU performs the operation prescribed and the output device delivers the result. Effectively what is being carried out is a process which starts off by developing or defining an initial population for generation of the test population from which the patients are extracted.
  • Fig. 3 shows how an initial population, after a number of generations, will provide a further population.
  • Fig. 4 shows how the genetic material is passed from parent to offspring and so on. All of this is well known to the geneticist and is included for information for those without such knowledge. Every individual, as is known, has two complete sets of alleles but passes on only one. The set that is passed on by one parent is usually not identical with either of the two original sets of this parent but is a mixture of both sets. The probability of two adjacent alleles, that is to say, two alleles of neighbouring loci within the same set, being transmitted together is given by the recombination fraction between the two loci. The recombination ratios have to be identified and are essential. This is visualised in Fig. 4.
  • step 20 With the set-up of the initial population.
  • step 21 the trait is introduced.
  • step 22 mating takes place and in step 23, we have procreation with recombination. Loci, alleles and recombinant ratios are illustrated in Fig. 5.
  • the first step is to define an initial population and to specify its characteristics. Then, it is necessary to specify the loci of reference markers. Then, the locus of at least one test locus is specified. This is obviously a speculative locus. This test locus is the locus where the disease locus will exist. These are therefore the specified loci, that is to say, the test locus and the loci of the markers. It will be appreciated that there could be any number of markers and similarly, there can be any number of test loci. Then, it is necessary to obtain the recombination fraction between all the specified loci, that is to say, of both the markers and the test locus or loci.
  • the recombination fraction for the test locus has to be derived from the recombination fraction of the two adjacent markers. For example, if the recombination fraction between two adjacent markers was 0.3, then if it was decided that the test locus was midway between the two markers, it could be assigned a recombination fraction of 0.15. Alternatively, if it was decided that it was closer to one of the markers, then its recombination fraction with that marker might be smaller and would be larger with the other marker.
  • a mutation is introduced at one locus.
  • this mutation can be introduced into more than one person. All those persons carrying the mutations are clones - they have exactly the same set-up. It is envisaged that it would be possible to change this so that populations could be set-up with more than one person having the mutation but with different sets of alleles. It will be appreciated that the bigger the initial population size, the better the experimental allele frequencies will match the ones in the actual population genetics files. At the end of the evolution, the allele frequencies should be essentially the same as the initially specified frequencies. The final output will contain all the patients within that test population which will have this mutation.
  • the population generation can be modified in many ways. For example, population stratification is allowed after the mutation has been introduced in the first iteration. However, stratification could also be provided before the mutation is introduced. Thus, it would be possible to start with an initial population and then after a certain number of generations had been formed, introduce the mutation.
  • Fig. 6 the patient and population generation is shown having been produced over a large number of generations. It started off with an initial population and some way through the generation of the population, the trait was introduced.
  • the initial population is the input parameter than can adjust the ratio of affected individuals so that you can end up with these forty thousand people having this particular genetic disorder. Having got this 40,000 affected, you would start off by choosing 100, i.e. the very small data set of Fig. 6, affected and conduct the actual gene hunting study theoretically and then possibly find that 100 is not enough and then you would try 200 and still find that this was not enough: this is the small data set of Fig. 6. Then, you would keep on increasing this patient population to a level where your results become reliable. Assuming it is less than the 254 patients who have been genotyped, you can move immediately to the actual gene hunting study. If it is more, you may require further patients to be genotyped, i.e. to get the larger data set of Fig. 6.
  • Fig. 7 illustrates the use of the transmission disequilibrium test (TDT) to determine the usefulness of the present invention, which considers parents who are heterozygous for an allele associated with the disease and evaluates the frequency with which that allele or its alternative is transmitted to affected offsprings.
  • TDT transmission disequilibrium test
  • the TDT has the advantage that it does not require data either on multiple affected family members or on unaffected siblings. This is a well known test procedure.
  • Fig. 9 charts the test population for various generations at one locus, namely locus 5, while Figs. 8(a), 8(b) and 8(c) show the frequency of occurrence at the various loci for different numbers of generation. It can be seen clearly from Fig. 9 that there is a clear level of linkage. You then have a phase of increasing linkage and a phase of decay.
  • TDT For the TDT at least three individuals have to be genotyped, that is the affected person and the two parents. Another disadvantage of the TDT is that for late-onset diseases (e.g., Alzheimer) the parents are usually no longer available for genotyping. An advantage of the TDT is that it usually has more 'power' than a simple likelihood-based linkage test.
  • TDT time tolive
  • the analysis could be carried out manually for this particular algorithm, but other algorithms are so computationally intensive that using a computer is essential.
  • TDT facility of the Genehunter software package provided by the Rockefeller Center. This software package like many others can be obtained freely and will execute on whatever machine it is installed on.
  • the input data has to be arranged in the required input format. For Genehunter this would include a personal identifier, the parents' personal identifier, gender information, affectation status and (phase unknown) allelic data.
  • the program is executed and provides output that lists the numbers of un/transmitted alleles, the corresponding chi-squared value and the so called p-value that is obtained from the chi-squared value.
  • the p-value is the probability that states how likely it would have been for this particular allele at this particular locus to have occurred in the observed way purely at random. Low p-values suggest that pure chance cannot explain the observed distribution of alleles and one might be led to believe that an underlying phenomenon could have contributed to this effect. One would hope that this underlying phenomenon is linkage.
  • An initial population was set up whose alleles were chosen at random.
  • the probability distributions according to which the alleles would be selected by the computer would be the same as the distributions of alleles observed in nature. We found empirically that the distribution of alleles changes only very little during the evolution, so that the final allele distribution of the theoretical population can be made to match the distribution of alleles observed in the real patient population.
  • One disease carrying patient was inserted into the initial population.
  • the ratio of the size of the initial population and the number of inserted disease carriers has a bearing on the ratio of simulated disease carriers, i.e. the theoretical patient population, at the end of the simulation and can therefor be chosen to match the observed ratio of disease carriers in the (real) population.
  • the test population evolved over a certain number of generations.
  • This number can be fixed by the experimenter if the age of the disease can be surmised. If no estimation can be made one could generate a couple of generations, some after a small number of generations and some after a larger number of generations. It is up to the experimenter to decide what 'small' and 'large' means in this context but the present invention can assist in this decision making process.
  • a test population was provided a certain size containing a sub-set of individuals that carried the disease allele which had been introduced into the initial population. This sub-set we call the theoretical patient population.
  • the second step in designing the experiment was to select the size of the real patient population that would be genotyped. Genotyping is expensive and experimenters would therefore like to keep this number as small as possible, while still giving reliable answers.
  • Out of the theoretical patient population we selected a small sub-set of families and used the Genehunter software. The condensed results (only the allele with the maximum of -log(p-value) at a locus) is represented in Figs. 10(a) and 10(b).
  • test loci inserts a large number of test loci. For example, in this particular experiment, three test loci were inserted between each pair of marker loci. In the particular example, one is placed close to one marker, the other is placed close to the other marker and a third test locus is placed between both markers. In this particular experiment, special provisions were made for the insertion of reference loci at the ends. These test loci would have only two types of alleles, namely, trait and non-trait.
  • the trait alleles can be inserted into one individual or into many, they could be inserted at one generation or over many generations, but all reference loci will be filled before the simulation is over.
  • the experimenter can then carry out his gene-hunting study assuming there is only one disease causing gene at reference locus A. This is done by picking out only patients that carry a trait at locus A and ignoring all patients that have no trait allele at locus A, despite having trait alleles at loci B and C.
  • the experimenter can then assume that the disease is caused by a single trait gene at reference locus B, ignoring trait genes at loci A and C. For this the 'theoretical patient population' does not have to be re-generated, only a different reference locus is projected out. This can be repeated for all assumed single locus disease loci.
  • the experimenter could then look at complex diseases that are caused if an individual has trait alleles at reference loci A and B, omitting individuals that have no trait alleles at locus A and locus B or individuals that have trait alleles at locus A but not at locus B and vice versa, etc.
  • the insertion of reference or test loci can be automated, and that the reference loci are picked for gene-hunting by the experimenter after the test population has been generated.
  • the advantage is that a population will have to be generated only once.
  • a disadvantage would be that the execution time will be longer than for a single reference locus simulation. The execution time will be less than several simulations for single reference loci.
  • the feedback from actual gene hunting studies will allow modifications of the manner in which the input data is used. If a theoretical patient population is produced whose size, relative to the test population, is less than the relative size of the actual patient population, in other words, namely, that the disease is more prevalent than expected, obviously, it would be necessary to alter the initial population or to alter the manner in which the population was generated by, for example, introducing the mutation in at least one additional locus so as to get a new theoretical patient population. Similarly, when the test population provided a theoretical patient population whose size relative to the test population is greater than the relative size of the actual patient population, then the size of the initial population can be increased and a new test population produced.
  • the invention has two advantages. The first is that it can theoretically check a gene hunting study and find out whether it could possibly ever work. If a proposed gene hunting study could be shown to be theoretically impossible to lead to a satisfactory result, then the proposed gene hunting study could be abandoned before it was started. Alternatively, the method of the present invention will allow the gene hunting study to be defined and designed in the correct manner.
  • the gene hunting study according to the present invention and indeed the practical aspects of an actual gene hunting study may not be carried out where the invention is carried out.
  • the invention could be contained on a server in a remote location and a research might simply input data to the server, which server would then either return to the researcher a test population and thus a patient population to allow the researcher carry out his or her theoretical gene hunting studies or alternatively, the server could provide the results of the theoretically gene hunting study to the researcher or investigator. It is estimated that this could all be done over the internet or other communications networks.
  • this invention can be carried out by a server or computer which will be programmed to provide various means for carrying out the invention such as means to generate a test population from an initial population of a certain size in which the test population is expressed in terms of its allelic data. There can also be means to input a mutation at at least one locus during generation of the test population or indeed at many loci. Similarly, there can be provided means to extract a theoretical patient population from the test population having regard to its allelic data. Further, there can be various means to carry out gene hunting studies on at least part of the theoretical patient population and to carry out a study testing methodology. It will also be noted from the comments above that means can be provided to carry out all of the methods of the present invention.
  • various aspects of the invention may be embodied on a computer that is running a program or program segments originating from a computer readable or usable medium, such medium including but not limited to magnetic storage media (e.g. ROMs, floppy disks, hard disks, etc.), optically readable media (e.g. CD-ROMs, DVDs, etc.) and carrier waves (e.g., transmissions over the internet).
  • a computer readable or usable medium such medium including but not limited to magnetic storage media (e.g. ROMs, floppy disks, hard disks, etc.), optically readable media (e.g. CD-ROMs, DVDs, etc.) and carrier waves (e.g., transmissions over the internet).
  • a functional program, code and code segments, used to implement the present invention can be derived by a skilled computer programmer from the description of the invention contained herein.
  • a computerised program may be provided providing program instructions which, when loaded into a computer, will constitute the means in accordance with the invention and that this computer program may be embodied on a record medium, a computer memory, a read only memory or carried on an electrical carrier signal.
EP01650098A 2001-08-31 2001-08-31 Un procédé pour définir des études de gene hunting Withdrawn EP1288835A1 (fr)

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Application Number Priority Date Filing Date Title
EP01650098A EP1288835A1 (fr) 2001-08-31 2001-08-31 Un procédé pour définir des études de gene hunting
JP2002085475A JP2003070500A (ja) 2001-08-31 2002-03-26 遺伝子探索計画方法及びシステム
PCT/IE2002/000129 WO2003019451A1 (fr) 2001-08-31 2002-09-02 Methode et systeme permettant de definir des etudes genetiques

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Cited By (2)

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US8030593B2 (en) 2006-03-23 2011-10-04 Nissan Motor Co., Ltd. Laser welding apparatus and method utilizing replaceable beam guide and calibration system
US8716622B2 (en) 2006-03-23 2014-05-06 Nissan Motor Co., Ltd. Apparatus and method for performing laser welding operations

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KR20200050992A (ko) * 2017-09-07 2020-05-12 리제너론 파마슈티칼스 인코포레이티드 인간 집단의 관련성을 예측하기 위한 시스템 및 방법

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US5781699A (en) * 1996-10-21 1998-07-14 Maxtor Corporation Method for optimization of channel parameters in a data storage device
WO2000028080A2 (fr) * 1998-11-10 2000-05-18 Genset Methodes, logiciel et appareils permettant d'identifier des regions genomiques hebergeant un gene associe a un trait detectable
WO2000042560A2 (fr) * 1999-01-19 2000-07-20 Maxygen, Inc. Methodes de fabrication de chaines de caracteres, de polynucleotides et de polypeptides

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US5781699A (en) * 1996-10-21 1998-07-14 Maxtor Corporation Method for optimization of channel parameters in a data storage device
WO2000028080A2 (fr) * 1998-11-10 2000-05-18 Genset Methodes, logiciel et appareils permettant d'identifier des regions genomiques hebergeant un gene associe a un trait detectable
WO2000042560A2 (fr) * 1999-01-19 2000-07-20 Maxygen, Inc. Methodes de fabrication de chaines de caracteres, de polynucleotides et de polypeptides

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Cited By (2)

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Publication number Priority date Publication date Assignee Title
US8030593B2 (en) 2006-03-23 2011-10-04 Nissan Motor Co., Ltd. Laser welding apparatus and method utilizing replaceable beam guide and calibration system
US8716622B2 (en) 2006-03-23 2014-05-06 Nissan Motor Co., Ltd. Apparatus and method for performing laser welding operations

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WO2003019451A1 (fr) 2003-03-06

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